USE CASES PUBLICATIONS BLOG

Real time kick detection applying an ultrasonic caliper featuring a downhole sonic speed measurement for calibration purposes

Recognition of variations in borehole shape in real time drilling allows the drilling engineer to actuate appropriate
counteractions to avoid costly failures, or to implement alterations in the drilling practices to optimize the shape of the
borehole and thus improve the drilling efficiency.

A Pattern-Based Framework for Events Recognition in Time Series Data

Recognizing the events in time series data, generated by a dynamic
system, is an essential step in analyzing the behavior of the underlying system
and improving its performance.

A Visual Analytics Approach to Segmenting and Labeling Multivariate Time Series Data

Industrial processes are often monitored via multiple sensors that record physical measurements over time.

Real Time Kick Detection and Also Increasing Ultrasonic Caliper Accuracy by Measuring Speed of Sound within Drilling Fluid in the Downhole Condition

To be alerted in determining early warning signs in well control is one of the most important to wellbore safety.

Formation Prediction Model based on Drill String Vibration Measurements Using Laboratory Scale Rig

Characteristics of formations usually cause changes in the drilling parameters such as weight on bit and drill string rotational speed as well as drill string dynamic behavior.

Formation Prediction Model based on Drill String Vibration Measurements Using Laboratory Scale Rig

Characteristics of formations usually cause changes in the drilling parameters such as weight on bit and drill string rotational speed as well as drill string dynamic behavior.

Intelligent Data Quality Control of Real-time Rig Data

There is an increasing requirement for centralized analysis of drilling data to improve performance.

Effect of Formations Compressive Strength on Drill String Vibrations

Vibrations are known as destructive loads and thus are leading to downhole fatigue failures, severe bottom hole assembly and bit wear and may cause wellbore instabilities.

Formation Changes Recognition by Real-time Monitoring of Drill String Vibrations and Mechanical Specific Energy

When talking about drill string vibrations, downhole fatigue failures and severe bit wear generally come first to the mind.

Intelligent Real-time Drilling Operations Classification Using Trend Analysis of Drilling Rig Sensors Data

Detection of oilwell drilling operations is an important step for drilling process optimization.

Using Neural Network Technique to Study the Effect of Formation Mechanical Properties on Dynamic Behavior of Drill String

Vibrations are caused by bit and drill string interaction with formations under certain drilling conditions. They are affected by different parameters such as weight on bit, torque on bit, rotary speed, mud properties, bottom hole assembly and bit design as well as by the mechanical properties of formations.

Laboratory Scale Control of Drilling Parameters to Enhance Rate of Penetration and Reduce Drill String Vibration

Drill string vibration and shock loads are known as destructive loads while drilling and are the reason for tool failure, lost time and reduction in rate of penetration.

ROP Modeling Using Neural Network and Drill String Vibration Data

Vibrations are caused by bit and drill string interaction with formations under certain drilling conditions.

Intelligent Real-time Drilling Operations Classification Using Trend Analysis of Drilling Rig Sensors Data

Detection of oilwell drilling operations is an important step for drilling process optimization. If drilling operations are classified accurately, detailed performance reports not only on drilling crews but also on drilling rigs can be produced.

Multivariate Time Series Classification by Combining Trend-Based and Value-Based Approximations

Multivariate time series data often have a very high dimensionality. Classifying such high dimensional data poses a challenge because a vast number of features can be extracted. Furthermore, the meaning of the normally intuitive term “similar to” needs to be precisely defined.

Scaling Of Flow Loops Based On The Bingham Plastic Model

Research has always been a very important part of the petroleum industry.

Automated System for Drilling Operations Classification Using Statistical Features

operations classification is one of the most needed tasks in the oil & gas industry. It provides the engineers with detailed information about what is happening on the rig site.

A Hybrid Multiple Classifier System for Recognizing Usual and Unusual Drilling Events

Up to very recently, the applications of machine learning in the oil & gas industry were limited to using a single machine learning technique to solve problems in-hand.